AIMC Topic: Deep Learning

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Intracranial vessel wall segmentation with deep learning using a novel tiered loss function incorporating class inclusion.

Medical physics
PURPOSE: To develop an automated vessel wall segmentation method on T1-weighted intracranial vessel wall magnetic resonance images, with a focus on modeling the inclusion relation between the inner and outer boundaries of the vessel wall.

Applying Deep Learning to Establish a Total Hip Arthroplasty Radiography Registry: A Stepwise Approach.

The Journal of bone and joint surgery. American volume
BACKGROUND: Establishing imaging registries for large patient cohorts is challenging because manual labeling is tedious and relying solely on DICOM (digital imaging and communications in medicine) metadata can result in errors. We endeavored to estab...

ALNett: A cluster layer deep convolutional neural network for acute lymphoblastic leukemia classification.

Computers in biology and medicine
Acute Lymphoblastic Leukemia (ALL) is cancer in which bone marrow overproduces undeveloped lymphocytes. Over 6500 cases of ALL are diagnosed every year in the United States in both adults and children, accounting for around 25% of pediatric cancers, ...

Scaffolding protein functional sites using deep learning.

Science (New York, N.Y.)
The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without n...

Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.

BMC infectious diseases
BACKGROUND: Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interp...

Decision effect of a deep-learning model to assist a head computed tomography order for pediatric traumatic brain injury.

Scientific reports
The study aims to measure the effectiveness of an AI-based traumatic intracranial hemorrhage prediction model in the decisions of emergency physicians regarding ordering head computed tomography (CT) scans. We developed a deep-learning model for pred...

Comparative Analysis of Aesthetic Emotion of Dance Movement: A Deep Learning Based Approach.

Computational intelligence and neuroscience
Dance is a unique art with the human body movement as the main means, but dance is not limited to the human body movement itself. Like any art, dance is the product of human social behavior and a romantic behavior of human thoughts and emotions in th...

Risk Analysis of A-H Share Connect Market Based on Deep Learning and BP Neural Network.

Computational intelligence and neuroscience
China's Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect programs make it possible for investors to trade stocks within specified limits through the two stock exchanges. The A-H share exchange stock market is crucial to the openi...

Bloom's Classification of Educational Objectives Based on Deep Learning Theory Teaching Design of Nursing Specialty.

Computational intelligence and neuroscience
Through the effective integration of various teaching resources, carry out the teaching design of "basic nursing technology" for the nursing specialty in the information environment based on Bloom's education objective classification. Select 200 nurs...

The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric.

BioMed research international
Pneumonia is a common lung disease that is the leading cause of death worldwide. It primarily affects children, accounting for 18% of all deaths in children under the age of five, the elderly, and patients with other diseases. There is a variety of i...